What is Google Cloud Dataflow used for?

Google Cloud Dataflow is a fully managed Google Cloud service for running stream and batch data processing pipelines written with Apache Beam, with autoscaling built in. It is a good fit for real-time event processing pipelines, batch ETL into a data warehouse and streaming analytics on log or IoT data.

How much does Google Cloud Dataflow cost?

Google Cloud Dataflow is a paid product with no free plan.

Is Google Cloud Dataflow open source?

No. Google Cloud Dataflow is proprietary (closed-source) software and can't be self-hosted. Open-source alternatives to Google Cloud Dataflow include Apache Spark and RisingWave.

What are some alternatives to Google Cloud Dataflow?

Google Cloud Dataflow competes with AWS Glue, Azure Data Factory and Databricks. For open-source options, see Enlisted's ranked list of open-source Google Cloud Dataflow alternatives.

Google Cloud Dataflow: features, pricing and alternatives

About Google Cloud Dataflow

Google Cloud Dataflow is a managed service for processing data in motion and at rest. Developers write pipelines with the Apache Beam programming model, and Dataflow runs them on Google Cloud, handling provisioning, scaling and execution so teams do not manage the processing infrastructure.

Google describes it as a fully managed streaming analytics service that cuts latency and processing time and keeps costs in check through autoscaling and real-time processing. The same Beam pipeline code can handle both streaming and batch workloads, which makes it a common choice for event ingestion, transformation and loading into destinations such as BigQuery.

Dataflow is a proprietary Google Cloud service with no self-hosted edition, although Apache Beam itself is open source and can run on other runners. Usage is billed under Google Cloud pricing, which is listed on the vendor's site.

Key features

Managed execution of Apache Beam pipelines
Unified stream and batch processing
Autoscaling of processing resources
Real-time data transformation
Integration with other Google Cloud services

Good fit for

→Real-time event processing pipelines
→Batch ETL into a data warehouse
→Streaming analytics on log or IoT data

Tags: google-cloud; apache-beam; streaming; batch-processing; etl; data-pipelines; autoscaling; cloud-service

Google Cloud Dataflow: questions and answers

What is Google Cloud Dataflow used for?: Google Cloud Dataflow is a fully managed Google Cloud service for running stream and batch data processing pipelines written with Apache Beam, with autoscaling built in. It is a good fit for real-time event processing pipelines, batch ETL into a data warehouse and streaming analytics on log or IoT data.
How much does Google Cloud Dataflow cost?: Google Cloud Dataflow is a paid product with no free plan.
Is Google Cloud Dataflow open source?: No. Google Cloud Dataflow is proprietary (closed-source) software and can't be self-hosted. Open-source alternatives to Google Cloud Dataflow include Apache Spark and RisingWave.
What are some alternatives to Google Cloud Dataflow?: Google Cloud Dataflow competes with AWS Glue, Azure Data Factory and Databricks. For open-source options, see Enlisted's ranked list of open-source Google Cloud Dataflow alternatives.